Summary
HTx will create a framework for next generation Health Technology Assessment (HTA) that supports patient-centred, societally oriented, and real-time decision-making for integrated healthcare throughout Europe. HTx will focus on therapeutic areas with high unmet need for which HTA information has to be provided on complex and personalised combinations of health technologies.
Based on a select number of relevant case studies, HTx will enhance methods for integrating evidence from RCTs and real-world data (RWD). HTx will also augment statistical and econometric methods for generating robust estimates of effectiveness and cost-effectiveness in order to support relevant HTA decision-making for these complex and personalised combinations of health technologies.
HTx will also contribute to improving methods to support personalised treatment advice fitted for sharing with patients and their physicians. This includes the development of statistical and econometric approaches and artificial intelligence/machine learning methods for forecasting treatment effects in specific groups of patients.
Simultaneously, in close collaboration with the European Network for HTA (EUnetHTA), HTx will improve synergies between regulatory agencies, HTA bodies and clinical guideline developers. This will include the translation of HTx methods into already existing European guidelines, most prominently those developed by EUnetHTA. HTx will also support initial efforts to discuss reimbursement and funding models that facilitate controlled access to and the pricing of these complex health technologies.
Finally, we will evaluate the transferability of HTx results into all EU Member Countries especially in Central and Eastern European (CEE) Countries and promote the dissemination of HTx results to the different European stakeholders with a special focus on the patient community.
Based on a select number of relevant case studies, HTx will enhance methods for integrating evidence from RCTs and real-world data (RWD). HTx will also augment statistical and econometric methods for generating robust estimates of effectiveness and cost-effectiveness in order to support relevant HTA decision-making for these complex and personalised combinations of health technologies.
HTx will also contribute to improving methods to support personalised treatment advice fitted for sharing with patients and their physicians. This includes the development of statistical and econometric approaches and artificial intelligence/machine learning methods for forecasting treatment effects in specific groups of patients.
Simultaneously, in close collaboration with the European Network for HTA (EUnetHTA), HTx will improve synergies between regulatory agencies, HTA bodies and clinical guideline developers. This will include the translation of HTx methods into already existing European guidelines, most prominently those developed by EUnetHTA. HTx will also support initial efforts to discuss reimbursement and funding models that facilitate controlled access to and the pricing of these complex health technologies.
Finally, we will evaluate the transferability of HTx results into all EU Member Countries especially in Central and Eastern European (CEE) Countries and promote the dissemination of HTx results to the different European stakeholders with a special focus on the patient community.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/825162 |
| Start date: | 01-01-2019 |
| End date: | 30-06-2024 |
| Total budget - Public funding: | 9 640 775,00 Euro - 9 640 775,00 Euro |
Cordis data
Original description
HTx will create a framework for next generation Health Technology Assessment (HTA) that supports patient-centred, societally oriented, and real-time decision-making for integrated healthcare throughout Europe. HTx will focus on therapeutic areas with high unmet need for which HTA information has to be provided on complex and personalised combinations of health technologies.Based on a select number of relevant case studies, HTx will enhance methods for integrating evidence from RCTs and real-world data (RWD). HTx will also augment statistical and econometric methods for generating robust estimates of effectiveness and cost-effectiveness in order to support relevant HTA decision-making for these complex and personalised combinations of health technologies.
HTx will also contribute to improving methods to support personalised treatment advice fitted for sharing with patients and their physicians. This includes the development of statistical and econometric approaches and artificial intelligence/machine learning methods for forecasting treatment effects in specific groups of patients.
Simultaneously, in close collaboration with the European Network for HTA (EUnetHTA), HTx will improve synergies between regulatory agencies, HTA bodies and clinical guideline developers. This will include the translation of HTx methods into already existing European guidelines, most prominently those developed by EUnetHTA. HTx will also support initial efforts to discuss reimbursement and funding models that facilitate controlled access to and the pricing of these complex health technologies.
Finally, we will evaluate the transferability of HTx results into all EU Member Countries especially in Central and Eastern European (CEE) Countries and promote the dissemination of HTx results to the different European stakeholders with a special focus on the patient community.
Status
SIGNEDCall topic
SC1-BHC-26-2018Update Date
26-10-2022
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Organisations
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| UNIVERSITEIT UTRECHT (Coördinator)
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| ACADEMISCH ZIEKENHUIS GRONINGEN
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| EUROPEAN ORGANISATION FOR RESEARCH AND TREATMENT OF CANCER AISBL
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| EURORDIS - EUROPEAN ORGANISATION FOR RARE DISEASES ASSOCIATION
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| KOBENHAVNS UNIVERSITET
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| MEDICAL UNIVERSITY SOFIA
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| NATIONAL INSTITUTE FOR HEALTH AND CARE EXCELLENCE
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| SYNAPSE RESEARCH MANAGEMENT PARTNERS SL
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| SYREON KUTATO INTEZET KORLATOLT FELELOSSEGU TARSASAG
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| TANDVARDS-OCH LAKEMEDELSFORMANSVERKET
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| UNIVERSIDAD POLITECNICA DE MADRID
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| UNIVERSITAET BERN
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| UNIVERSITAIR MEDISCH CENTRUM UTRECHT
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| UNIVERSITEIT MAASTRICHT
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| UNIVERSITY OF YORK